Added By Tom Bleier:
After further discussions, it was determined analytics should be broken up into three categories.
Web Analytics - This area deals with the tracking of user movements and experiences on the web site. Examples would be: Do people abandon the web site at a specifc spot? If someone enters a custom size, do they buy a custom size, stock size or nothing? How much time is someone spending on the site? On what screen are customers most likely to use "Live Chat"? Do customers use all the features of the web site, such as, sharing carts? Do we capture all the information of something the customer couldn't find? These answers can be accomplished with outside tools, such as, Google Analytics and Clicktale or with some programming to "trap" specific data. It was determined at this stage this is a lower priority and will ultimately fall to the UI interface person/people to manage.
Internal Facing Data Mining - This category of analytics is information that is collected within our current databases and is not needed for immediate action on the web, but used to make business/marketing decisions internally. Examples would be: Discovering new items we need to quote that we currently do not. Monitoring custom quotes of BAGS, FURN, SOR, etc... to determine if we need to add an item to stock. Montioring our customers business to see if they are having a spike or lull in a specific category. Seeing who from a company is using the web. Looking at a customer's "Samples" volume. This collection of information already exists and will only be enhanced once the web is live, but at this time requires minimal (if any) "web team" time to push forward.
Customer Facing Data Mining - The final area of analytics is data that is to be displayed to the customer that does not necessarily deal with search results, but allows them to increase their business with Laddawn making the web site an indispensible hub for their daily work. Examples would be: Reminding the customer a sample was sent. Pointing customers to a video tutorial on custom quoting over the web, if they only buy stock over the web. Most importantly, predicting what orders or quotes might be coming up for them based on older quotes and orders. It was determined the best way to decide what is the most relevant customer facing data that needs to be mined and displayed to our customers to increase their sales is to figure out how our best senior customer relationship partners figure who they need to call and when, to assure themselves of the best returns for their time. Once we have determined what it is to show the customer, we will still have the open question of how is it best to display this information; via the experience thread, as an e-mail, at the bottom of a specific page, or to build a dashboard. - TEB
==============================================================================================================================